Nonlinear adaptive RBFNN control of a one-link flexible manipulator

Author

Maouche, Amin Riad ; Attari, Mokhtar

Author_Institution

Lab. of Instrum., Houari Boumedien Univ., Algiers, Algeria

fYear

2010

fDate

3-5 Oct. 2010

Firstpage

165

Lastpage

170

Abstract

This paper describes a hybrid approach to the problem of controlling flexible link manipulators in the face of both structured and unstructured uncertainties. First, a nonlinear controller based on the equations of motion of the robot is elaborated. Its aim is to produce a stable control. Then, an adaptive RBF neural controller is implemented to compensate structured and unstructured uncertainties. Efficiency of the new controller obtained by combining the two control laws is tested facing an important variation of the dynamic parameters of the flexible manipulator and compared to a classical nonlinear controller. Simulation results show the effectiveness of the proposed control strategy.

Keywords

adaptive control; flexible manipulators; neurocontrollers; nonlinear control systems; radial basis function networks; uncertain systems; nonlinear adaptive RBFNN control; one-link flexible manipulator; robot motion equation; unstructured uncertainties; Adaptation model; Artificial neural networks; Manipulator dynamics; Mathematical model; Torque; Trajectory; Adaptive control; RBF neural network; flexible-link manipulator; nonlinear control;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine and Web Intelligence (ICMWI), 2010 International Conference on

Conference_Location

Algiers

Print_ISBN

978-1-4244-8608-3

Type

conf

DOI

10.1109/ICMWI.2010.5647944

Filename

5647944